Review on Lossless Image Compression Techniques for Welding Radiographic Images

Abstract

Recent development in image processing allows us to apply it in different domains. Radiography image of weld joint is one area where image processing techniques can be applied. It can be used to identify the quality of the weld joint. For this the image has to be stored and processed later in the labs. In order to optimize the use of disk space compression is required. The aim of this study is to find a suitable and efficient lossless compression technique for radiographic weld images. Image compression is a technique by which the amount of data required to represent information is reduced. Hence image compression is effectively carried out by removing the redundant data. This study compares different ways of compressing the radiography images using combinations of different lossless compression techniques like RLE, Huffman.

Lossless Image Compression using Adaptive Predictive Coding of Selected Seed Values

“…Basically, the data compression based on removing or eliminating the redundancy(s) as much as possible. In image case, the redundancy can be categorized into statistical redundancy and psychovisual redundancy, for the former this encompass the lossless image compression, while for the latter only or with the former this encompass the lossy image compression, for more details see [1][2][3][4][5][6][7][8] .…”

Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model

“…Generally, it is possible to do lossless compression with techniques such as Huffman coding, Arithmetic coding, Lempel-Ziv, Differential Pulse Code Modulation and Multiresolution techniques; but most of these methods leads to limited compression rate results. Reviews of medical image compression techniques can be found in [1]- [7].…”